Model Card for xlm-roberta-large-squad2-csfever_v2-f1
Model Details
Model for natural language inference trained as a part of bachelor thesis.
Uses
Transformers
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("ctu-aic/xlm-roberta-large-squad2-csfever_v2-f1")
tokenizer = AutoTokenizer.from_pretrained("ctu-aic/xlm-roberta-large-squad2-csfever_v2-f1")
Sentence Transformers
from sentence_transformers.cross_encoder import CrossEncoder
model = CrossEncoder('ctu-aic/xlm-roberta-large-squad2-csfever_v2-f1')
scores = model.predict([["My first context.", "My first hypothesis."],
["Second context.", "Hypothesis."]])
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from sentence_transformers import SentenceTransformer model = SentenceTransformer("ctu-aic/xlm-roberta-large-squad2-csfever_v2-f1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]